1. Field of the Invention
This invention relates to the field of computer vision, and in particular to a system and method for counting vehicles on roadways during periods of reduced visibility.
2. Description of Related Art
Cameras are conventionally used to monitor traffic flow. Coupling a video processing system to cameras that monitor traffic flow can facilitate traffic flow analysis and other traffic related studies. Such analyses and studies typically require a determination of the number of vehicles traveling on a particular stretch of road, the number of vehicles entering or exiting a road at a particular intersection, the number of vehicles exhibiting a particular driving pattern, and so on. In order to provide an accurate count of vehicles, each vehicle must be distinguished from each other vehicle, and often the path of each discretely distinguished vehicle must be determined, at least for some finite time or distance.
Image recognition systems are conventionally used to distinguish each vehicle in a video image of a road scene. For example, in a typical image recognition system, an edge-detection algorithm may be used to distinguish shapes in an image; a motion-detection algorithm may be used to distinguish moving shapes in a series of images, and to group lower-level shapes into larger shapes, based on common movement; and a pattern recognition algorithm may be used to identify which of the moving shapes correspond to vehicles. Once the shape is identified as being a vehicle, the location of this particular vehicle in prior and future images can be determined, thereby determining the path of the identified vehicle.
Identifying vehicles in reduced visibility situations, particularly after dark, is particularly problematic. If the monitored segment of roadway is brightly lit, the conventional image recognition algorithms generally operate effectively, but if the segment is not brightly lit, the conventional image recognition algorithms are unable to accurately distinguish vehicles. In a dark environment, colors and/or luminance differences are not distinguishable, and the conventional edge-detection algorithms fail to accurately distinguish shapes that correspond to the shape of the moving vehicles. The conventional motion-detection algorithm will also exhibit anomalous behavior, as items will appear and disappear in sequential images, depending upon their illumination by passing vehicles' headlights. Although pattern-recognition techniques may be employed to distinguish vehicles by distinguishing pairs of uniformly moving headlights, such techniques are susceptible to misidentifications caused by reflections, such as the reflection of headlights on a wet roadway at night.
Typically, to facilitate vehicle identification in reduced visibility systems, infrared cameras or night-vision cameras are employed. Such a deployment of infrared or night-vision cameras increase the cost of such vehicle monitoring systems. If a video system is already deployed, the cost of adding infrared or night-vision devices includes the cost of the additional cameras and their installation, as well as the cost to access and modify the existing installation to facilitate the installation.